Using our techniques for extracting approximate non-tandem repeats[1] on well constructed maximal models, we derive an algorithm to find common motifs of length P that occur in N sequences with at most D differences under the Edit distance metric. We compare the effectiveness of our algorithm with the more involved algorithm of Sagot[17] for Edit distance on some real sequences. Her method has not been implemented before for Edit distance but only for Hamming distance[12,20]. Our resulting method turns out to be simpler and more efficient theoretically and also in practice for moderately large P and D.
CITATION STYLE
Adebiyi, E. F., & Kaufmann, M. (2002). Extracting common motifs under the levenshtein measure: Theory and experimentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2452, pp. 140–156). Springer Verlag. https://doi.org/10.1007/3-540-45784-4_11
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